R-Based Visualization Techniques for Task-Based Applications

Performance analysis workflow that combines the power of the R language (and the tidyverse realm) and many auxiliary tools to provide a consistent, flexible, extensible, fast, and versatile framework for the performance analysis of task-based applications that run on top of the StarPU runtime (with its MPI (Message Passing Interface) layer for multi-node support). Its goal is to provide a fruitful prototypical environment to conduct performance analysis hypothesis-checking for task-based applications that run on heterogeneous (multi-GPU, multi-core) multi-node HPC (High-performance computing) platforms.


Reference manual

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0.7.0 by Lucas Leandro Nesi, 3 months ago


Report a bug at https://github.com/schnorr/starvz/issues

Browse source code at https://github.com/cran/starvz

Authors: Lucas Mello Schnorr [aut, ths] , Vinicius Garcia Pinto [aut] , Lucas Leandro Nesi [aut, cre] , Marcelo Cogo Miletto [aut] , Guilherme Alles [ctb] , Arnaud Legrand [ctb] , Luka Stanisic [ctb] , Rémy Drouilhet [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports methods, grDevices, stats, utils, magrittr, dplyr, ggplot2, tibble, rlang, tidyr, patchwork, purrr, readr, stringr, yaml, lpSolve, gtools, data.tree, RColorBrewer, zoo, Rcpp, arrow

Suggests testthat, flexmix, car, viridis

Linking to Rcpp, BH

System requirements: C++, arrow package with gzip codec, StarPU

See at CRAN